Implement knowledge mining and document intelligence solutions →easyMultiple ChoiceObjective-mapped

AI-102 Practice Question: Implement knowledge mining and document intelligence solutions

Exhibit

Refer to the exhibit.
```json
{
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.EntityRecognitionSkill",
      "name": "#1",
      "description": "Extract organizations",
      "context": "/document",
      "categories": ["Organization"],
      "inputs": [
        {
          "name": "text",
          "source": "/document/content"
        }
      ],
      "outputs": [
        {
          "name": "organizations",
          "targetName": "organizations"
        }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.KeyPhraseExtractionSkill",
      "name": "#2",
      "description": "Extract key phrases",
      "context": "/document",
      "inputs": [
        {
          "name": "text",
          "source": "/document/content"
        }
      ],
      "outputs": [
        {
          "name": "keyPhrases",
          "targetName": "keyPhrases"
        }
      ]
    }
  ]
}
```

Refer to the exhibit. You have a skillset with two skills. You run the indexer and find that the output field 'organizations' is empty for documents that clearly contain organization names. The 'keyPhrases' output is populated correctly. What is the most likely cause of the issue?

⚠ Common exam trap

Candidates often assume the 'keyPhrases' skill working correctly implies all skills are fine, overlooking that Entity Recognition is language-dependent and requires explicit 'defaultLanguageCode' configuration, while 'keyPhrases' is more robust across languages.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

The skill is not configured with a 'defaultLanguageCode' and the documents are not in English.

The 'keyPhrases' output is populated correctly, indicating the text extraction and overall pipeline are functional. The Entity Recognition skill requires a 'defaultLanguageCode' to correctly identify entities; if it is not set and the documents are not in English, the skill may fail to extract organizations, resulting in an empty 'organizations' field. This is a known behavior where the skill defaults to English and cannot process other languages without explicit configuration.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
The skill's 'name' property is set to '#1', which is invalid.
Why it's wrong here
The name can be any string; '#1' is allowed.
✓
The skill is not configured with a 'defaultLanguageCode' and the documents are not in English.
Why this is correct
EntityRecognitionSkill needs a language hint to perform correctly for non-English languages.
✗
The 'categories' property is misspelled; it should be 'entityCategories'.
Why it's wrong here
The property 'categories' is correct for EntityRecognitionSkill.
✗
The input source '/document/content' is incorrect; it should be '/document/text'.
Why it's wrong here
The input source depends on the document parsing; '/document/content' is a common field.

Go deeper

AI-102 Practice Question: Implement knowledge mining and document intelligence solutions

Exhibit

Why each option matters

Option-by-option breakdown

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